In an attempt to ensure the proper operation of locomotives in the railroad fleet, the United States government has mandated that active locomotives undergo inspections at maximum intervals of 92 days. As a result of this mandate and in order to minimize the downtime of active locomotives, the routine maintenance of these locomotives are typically scheduled to evolve around this 92-day inspection cycle. For example, the engine oil and filters are routinely drained or changed every 92 or 184 days and oil specimens are sent to an outside laboratory for analysis. The resultant data from this analysis is entered into an operations database, wherein the operations database includes the results of previously analyzed specimens. A field service engineer then reviews and evaluates the data to determine if the data exceeds established parameters. If any limits are exceeded, the field service engineer takes the prescribed action responsive to the limit(s) exceeded. Unfortunately however, the current approach toward maintaining these locomotives includes several undesirable limitations.
One such limitation involves the inability to effectively diagnose some existing problems that may initially represent themselves as analytical values approach a predefined limit. For example, consider the situation where a problem exists but is not severe enough at the time the oil sample is taken to cause oil analysis values to exceed established limits. When the field service engineer is evaluating the resultant data from the laboratory analysis to determine whether any corrective action is required for a particular locomotive, proportionate corrective action will be decided upon in a manner responsive only to those values that have exceeded the prescribed limits. For oil analysis data that fall within the prescribed limits, the field service engineer does not perform or recommend a corrective action. Thus, the problem would not be detected until the locomotive has exceeded a prescribed limit or until the next scheduled maintenance occurs.
Another limitation involves the inability to identify possible pending anomalies. For example, consider the situation where a problem does not yet exist, but is becoming more probable due to the age or operating environment of the locomotive. Because the oil analysis data being reviewed by the field service engineer is most responsive only to the most recently drawn oil sample, the data offers little or no information pertaining to the condition of the oil drained from the same unit during previous maintenance. Information pertaining to the prior performance of the locomotive is not factored into the field service engineer's consideration of the engine and engine oil condition. Thus, any degradation in operation of the locomotive prior to the most recent maintenance is typically not considered when corrective action is being contemplated. This is undesirable because some locomotives, such as older locomotives or locomotives that are operated in harsh environments may require more frequent maintenance. As above, the anomaly would not be detected until the locomotive has exceeded the limit or until the next scheduled maintenance occurs. Both of these issues act to increase the cost of maintaining the locomotive and to decrease the life expectancy of the locomotive.